Quality Assurance: Best Practices in Clinical SAS® Programming

NESUG 2012 Management, Administration and Support Quality Assurance: Best Practices in Clinical SAS® Programming Parag Shiralkar eClinical Solutions, a Division of Eliassen Group Abstract SAS® programmers working on clinical reporting projects are often under constant pressure of meeting tight timelines, producing best quality SAS® code and of meeting needs of customers. As per regulatory guidelines, a typical clinical report or dataset generation using SAS® software is considered as software development. Moreover, since statistical reporting and clinical programming is a part of clinical trial processes, such processes are required to follow strict quality assurance guidelines. While SAS® programmers completely focus on getting best quality deliverable out in a timely manner, quality assurance needs often get lesser priorities or may get unclearly understood by clinical SAS® programming staff. Most of the quality assurance practices are often focused on ‘process adherence’. Statistical programmers using SAS® software and working on clinical reporting tasks need to maintain adequate documentation for the processes they follow. Quality control strategy should be planned prevalently before starting any programming work. Adherence to standard operating procedures, maintenance of necessary audit trails, and necessary and sufficient documentation are key aspects of quality. This paper elaborates on best quality assurance practices which statistical programmers working in pharmaceutical industry are recommended to follow. These quality practices are directly referred from the regulatory guidance and are illustrated with examples in this manuscript. Introduction: Programmers working in pharmaceutical industry perform various tasks including but not limited to data management programming, data validation and mapping, data analysis, report generations, and performing queries on data. Although programming staff does lot of clinical as well as statistical programming, because of de-facto use of SAS® software in statistical programming such programming staff is often referred as ‘SAS® programmers’. Some of the tasks in which programmers are involved are more ‘supplemental’ tasks to support the data management function. These tasks include data validation, data queries, and edit check programming. On a biostatistics side, programmers are involved in more analysis oriented tasks like generation of statistical reports, and development of analysis datasets. Time spent by SAS® programmers on these assignments depends on various factors like complexity of tasks, quality expectations, and availability of time to complete the request. Even though in most of the cases programmers meet customer expectations by providing best quality results, they often tend to loose their focus on bigger picture in terms of maintaining process integrity. In following discussion, we will look into some of the core process documentation in clinical trial and see how the SAS® programming is related to those processes. 1 NESUG 2012 Management, Administration and Support Clinical Trial Core Documentation: Every sponsor organization conducting or sponsoring a clinical trial is required to maintain a ‘trial master file’ or TMF. This core set of documentation consists of lot of trial specific regulatory documentation. This requirement is enforced by regulatory authorities to ensure that clinical trial sponsoring organizations follow regulatory guidance and good clinical practices (GCPs). In case of regulatory audit and submissions, TMF is the core focus of both internal and external assessments. TMF includes lot of core documentation of clinical trial. Since the work of SAS® programmers are primarily focused on data analysis and reporting, let’s look into some of the core documentation related to data management and biostatistics functions which is part of TMF: Data Management Plan: Data management plan or DMP consists of lot of details relevant to data collection, storage, archival, and overall data management. This includes the data standards used, data integrity checks and validation mechanisms used to manage the data. Programmers working on edit checks or data queries are often required to refer to data management plan for more input. At the same time, in many circumstances data management or clinical programming deliverables may get included as an input to data management plan. Statistical Analysis Plan: This document often referred as SAP, elaborates on details of statistical analyses and reporting of the clinical trial data. SAP includes details including but not limited to analysis populations, windowing, imputations, baseline computations, and guidelines for other complex analyses. List of tables and table shells which outline the guidelines of tabular presentation needs for trial reporting are considered as a part of SAP. Any SAS® programs developed to produce these tabular presentations are required to follow the software development life cycle (SDLC) principals and related regulatory guidelines as listed in references. While following SDLC, programmers are required to document the detailed algorithm along with functional specifications. Many sponsors include such documentation along with quality check documentation as a part of trial master file. So, looking at the above core documentation of clinical trial, it is evident that the scope of programming work SAS® programmers do in clinical trial in not confined to a micro level within biostatistics or data management functions. Rather, it is part of a broader requirement of trial level documentation and processes which get closely monitored and audited by regulatory authorities. While programmers focus on ‘what needs’ to be produced, there should be sufficient focus on documenting ‘how it is produced and quality checked’. Although these two perspectives are ‘required’, how much focus should programmer give on these two aspects depends on management guidelines and the time and budget constraints imposed on the programming staff. Regardless of such constraints, it is strongly recommended that programmers pay necessary attention to documenting functional specifications and quality check related details as such details are part of trial master file of the clinical trial. 2 NESUG 2012 Management, Administration and Support Overall clinical process where SAS® programming is a core focus is shown below: Clinical trial sponsor management defines the standard operating procedures and work instructions related to programming function by keeping above processes and regulatory guidance in considerations. While working on any assignment, SAS® programming staff is required to follow such processes, operating procedures and work instructions. Quality: How is it perceived? Looking at above macro perspective, ‘quality’ of programming deliverable has multiple dimensions and performance of programming service is perceived by different stakeholders in clinical trial in different manner. Customers, management, and quality assurance are key stakeholders who get impacted with quality of programming deliverables. • Customers: Depending on type of programming work programming staff is involved in, customers of programmers could be data managers, biostatisticians, medical writers, clinicians, or other analyst staff including pharmacokinetics and pharmacometric analysts. In most of the cases clinicians and statisticians are key customers of statistical programmers. In other words 3 NESUG 2012 Management, Administration and Support clinicians and biostatisticians are primarily interested in the quality and timely delivery of reports and datasets produced by programmers. These customers perceive quality of programming service and staff by measuring how efficiently and in timely manner do programmers produce the outputs. Customers- Statistician and Quality Assurance Clinician Key Indicator- Sufficient Key indicators- Quality, and documentation reflecting timely delivery process adherence. SAS® Programmer- Work Quality Management- Key Indicators- Customer satisfaction, cost, knowledge management • Management: When it comes to quality of programming service, management perceives it from a macro perspective and considers customer satisfaction and cost effectiveness of the service. Quality of output and timely delivery as perceived by customers leads to customer satisfaction. However, cost effectiveness always puts a constraint in terms of how many programming resources can be utilized for certain tasks. Such budget constraints often have conflicting effect on programming function. • Quality Assurance: While programming function and staff pays more attention to efficiency and cost, quality assurance needs often get lesser focus. In earlier section we looked at the overall clinical reporting process. The focus of Quality Assurance is to ensure that programming function and staff adheres to the process defined by management. This process adherence is often measured in terms of maintenance of process documentation and timely actions taken by programming staff over the course of trial. 4 NESUG 2012 Management, Administration and Support Difference Between Quality Control (QC) and Quality Assurance (QA): Quality control of programming process focuses more on ensuring efficient output delivery and ensures satisfaction of key customers of statistical programming function. While ensuring efficient delivery, programmers may not necessarily follow the processes perfectly. Quality assurance on the other hand focuses on process adherence. If programming

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